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SASInstitute Modeling Using SAS Visual Statistics Sample Questions:

1. Given a scenario, what condition makes models comparable in SAS Visual Statistics?

A) If they have different sample sizes
B) If they use the same dataset and response variable
C) If they use different response variables
D) If they use different link functions

2. Which equation does NOT represent a linear model? Note: bi are parameters and Xi are variables.

A) y = b0 + b1X1 + b2X2 + b3(X1X2)
B) y = b0 + b1X1 + (b2/b1)X2
C) y = b0 + b1X1 + b2X2
D) y = b0 + b1X1 + b2X1 3

3. In model assessment, why might you need to assess residuals and other model diagnostics to choose an appropriate distribution and link function?

A) To determine the order of predictor variables in the model
B) To ensure that predictor variables are not highly correlated
C) To verify if the chosen model assumptions are met and make adjustments if necessary
D) To calculate the p-values of predictor variables

4. When building a Generalized Linear Model in SAS Visual Statistics, which link function is available?

A) Poisson
B) Log
C) Negative Binomial
D) Gaussian

5. In linear regression modeling, what roles are typically assigned to variables?

A) Dependent, Independent, and Categorical
B) Input, Target, and Nominal
C) Intercept, Slope, and Error
D) Predictor, Response, and Interaction

Solutions: